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DeepSeek Reasoner vs DeepSeek-R1-0528

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
DeepSeek Reasoner vs DeepSeek-R1-0528: Benchmarks, Pricing & Speed Comparison

DeepSeek Reasoner di DeepSeek e DeepSeek-R1-0528 di DeepSeek sono due modelli di IA di riferimento. DeepSeek Reasoner offre una finestra di contesto di 1M token a $0.28/$0.42 per milione di token, mentre DeepSeek-R1-0528 mette a disposizione 128K token di contesto a $0.55/$2.19 per milione di token. Di seguito analizziamo benchmark, latenza e costi.

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DeepSeek

DeepSeek Reasoner

Ragionamento a Pesi Aperti

DeepSeek Reasoner di DeepSeek è un modello di IA progettato per il ragionamento Chain-of-Thought a pesi aperti ad alta efficienza algoritmica, con finestra di contesto da 1M, velocità di 52 token/s, indice di intelligenza di 54/100 e tariff

Intelligence Index54 / 100
Input Token:

$0.28 / 1M

Output Token:

$0.42 / 1M

Context Window:

1M tokens

SWE-bench Verified:

56.5%

DeepSeek

DeepSeek-R1-0528

Ragionamento a Pesi Aperti

DeepSeek-R1-0528 di DeepSeek è un modello di IA progettato per il ragionamento Chain-of-Thought a pesi aperti ad alta efficienza algoritmica, con finestra di contesto da 128K, velocità di 48 token/s, indice di intelligenza di 52/100 e tarif

Intelligence Index52 / 100
Input Token:

$0.55 / 1M

Output Token:

$2.19 / 1M

Context Window:

128K tokens

SWE-bench Verified:

51.8%

Differenze Chiave a Colpo d’Occhio

  • DeepSeek Reasoner is 3.6x cheaper for API usage (input + output tokens combined).
  • DeepSeek Reasoner has a larger context window (1M vs 128K tokens).
  • DeepSeek Reasoner is faster at 52 tok/s vs 48 tok/s.
  • DeepSeek Reasoner leads on SWE-bench coding (56.5% vs 51.8%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureDeepSeek ReasonerDeepSeek-R1-0528
Intelligence Index
Composite reasoning & knowledge score (0-100)
5452
Provider
DeepSeekDeepSeek
Input Price
Cost per million input tokens
$0.28 / 1M$0.55 / 1M
Output Price
Cost per million output tokens
$0.42 / 1M$2.19 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.12 / 1M$0.43 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text128K tokens~192 A4 pages of text
Max Output Tokens
Per single request
33K8K
Throughput Speed
Tokens generated per second
52 tok/s48 tok/s
SWE-bench Verified
Real-world software engineering
56.5%51.8%
GPQA Diamond
Graduate-level reasoning
76.5%74.2%
Cached Input Price
Prompt caching discount per 1M tokens
$0.03 / 1M$0.14 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework
Coding
DeepSeek Reasoner
+4.7% SWE-bench lead
Cost
DeepSeek Reasoner
3.6x cheaper monthly runtime
Speed
DeepSeek Reasoner
+8% faster generation
Context
DeepSeek Reasoner
1M tokens window

Punteggi Benchmark Verificati

Official evaluation metrics verified by independent third-party research labs.

DeepSeek ReasonerDeepSeek-R1-0528
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

56.5%vs51.8%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

76.5%vs74.2%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

86.2%vs85.6%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1368ptsvs1355pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

13.5%vs12%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

37.5%vs34%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

35%vs31.8%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

58.5%vs54%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

87.5%vs85%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

85%vs78%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

52 tok/s vs48 tok/s

Latenza e Tempo di Risposta

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
DeepSeek Reasoner0.82s
DeepSeek-R1-05280.90s
Est. End-to-End Response (500 tokens)TTFT + generation time
DeepSeek Reasoner10.44s
DeepSeek-R1-052811.32s

Simulatore Interattivo dei Costi Token

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
DeepSeek Reasoner Monthly API Bill
$0.84 / month
$0.28/1M in · $0.42/1M out
DeepSeek-R1-0528 Monthly API Bill
$3.01 / month
$0.55/1M in · $2.19/1M out
DeepSeek Reasoner saves approximately $2.17 / month (72%) under this workload.3.6x Savings

DeepSeek Reasoner · Strengths & Key Advantages

  • Finestra di contesto da 1M con capacità massima di output fino a 33K token (SWE-bench Verified 56.5% · GPQA Diamond 76.5%)
  • Throughput elevato di 52 token/secondo con latenza al primo token (TTFT) di soli 820 ms
  • Pesi aperti (671B Total (37B )) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama
Considerations & Trade-offs
  • Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
  • Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

DeepSeek-R1-0528 · Strengths & Key Advantages

  • Finestra di contesto da 128K con capacità massima di output fino a 8K token (SWE-bench Verified 51.8% · GPQA Diamond 74.2%)
  • Throughput elevato di 48 token/secondo con latenza al primo token (TTFT) di soli 900 ms
  • Pesi aperti (671B (37B MoE)) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama
Considerations & Trade-offs
  • Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
  • Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricDeepSeek ReasonerDeepSeek-R1-0528
Cost per Task
Estimated USD to finish one task
$0.22$0.62
Output Tokens / Task
Tokens generated per task
45K45K
Reasoning Tokens / Task
Thinking tokens burned per task
26K25K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

FeatureDeepSeek ReasonerDeepSeek-R1-0528
Official API Model ID (SDK)deepseek-reasonerdeepseek-reasoner
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2025-122025-05
Knowledge CutoffSeptember 2025March 2025
ArchitectureReinforcement-Learned Reasoning MoEOpen-Weights Reasoning MoE
Parameters671B Total (37B Active)671B (37B active MoE)
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed CloudUnlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)Flat rate ($0.28/1M in) across full 1000K windowFlat rate ($0.55/1M in) across full 128K window
Prompt Cache Policy & TTLAutomatic prefix caching at $0.028/1M (no extra cache-write fee)Automatic prefix caching at $0.14/1M (no extra cache-write fee)
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 416 GB VRAM (4-bit Quantized) · 1443 GB VRAM (Native BF16)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 416 GB VRAM (4-bit Quantized) · 1443 GB VRAM (Native BF16)
Safety & Frontier ClassificationOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestexttext
Output Modalitiestexttext

DeepSeek Reasoner vs DeepSeek-R1-0528: Risposte Rapide (FAQ)

Which is more intelligent, DeepSeek Reasoner or DeepSeek-R1-0528?

DeepSeek Reasoner is more intelligent. It scores 54 compared with 52 on the composite Intelligence Index.

Which model is faster?

DeepSeek Reasoner is faster, generating 52 tokens per second compared with 48 tokens per second.

Which model is cheaper to run?

DeepSeek Reasoner is cheaper at $0.12 per 1M tokens blended, compared with $0.43 (7:2:1 cache:input:output ratio).

Which model has lower latency?

DeepSeek Reasoner has lower latency, with a time to first token of 0.82s compared with 0.90s.

Which model has a larger context window?

DeepSeek Reasoner has a larger context window, supporting 1M tokens compared with 128K tokens.

Verdetto

Sia DeepSeek Reasoner (Ideale per il ragionamento Chain-of-Thought a pesi aperti ad alta efficienza algoritmica, sistemi RAG aziendali e integrazioni API scalabili.) sia DeepSeek-R1-0528 (Ideale per il ragionamento Chain-of-Thought a pesi aperti ad alta efficienza algoritmica, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: DeepSeek Reasoner guida nei benchmark di ragionamento e programmazione, DeepSeek Reasoner garantisce una generazione più rapida e DeepSeek Reasoner offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, DeepSeek Reasoner o DeepSeek-R1-0528?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale DeepSeek Reasoner. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra DeepSeek Reasoner e DeepSeek-R1-0528?+

DeepSeek Reasoner costa $0.28 / $0.42 per milione di token di input/output, mentre DeepSeek-R1-0528 costa $0.55 / $2.19. Nel costo combinato, DeepSeek Reasoner risulta più economico.

Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+

DeepSeek Reasoner supporta 1M token di contesto contro 128K token di DeepSeek-R1-0528, mentre DeepSeek Reasoner offre una velocità di generazione superiore.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

Fonti ufficiali: Documentazione API ufficiale di DeepSeek e DeepSeek, schede di sistema e benchmark indipendenti (2026).